Increasing trust formation and reduce oversight costs for autonomous agents

ABSTRACT

An autonomous agent operating method, system, and computer program product, including configuring an autonomous agent for a task, launching the autonomous agent with an initial update interval, the update interval determining a frequency of the autonomous agent reporting results to a human user for review, measuring the trust level of human user in a performance of the autonomous agent, and dynamically adjusting the update interval based on this measured trust.

BACKGROUND

The present invention relates generally to an autonomous agent operatingmethod, and more particularly, but not by way of limitation, to asystem, method, and computer program product for increasing trustformation and reducing oversight costs for autonomous agents.

Autonomous agents can perform long running tasks on behalf of a humanuser (e.g. search, service procurement, automatic bidding, resourcescheduling, etc.). Once launched, the agent's behavior is often notvisible until results are returned or the human engages in activeinspection of current agent state. This can reduce the trust that thehuman owner has in the agent.

To compensate for this, an agent can be programmed to give frequentstatus updates on task progress (e.g., number of sites explored, numberof contracts pending, amount of capital remaining for resource purchase,etc.).

While frequent status updates can increase trust, this can lead to highmonitoring costs for the human owner and an erosion of the perceivedvalue of agent autonomy. Conversely, infrequent status updates reducethe cost of monitoring but can lead to both reductions in trust andultimately suboptimal results since there are fewer opportunities forcorrective actions by the human owner.

Balancing this tradeoff properly over time can maximize trust whileminimizing the overhead of providing oversight. Thereby, the inventorshave identified a need in the art that requires a mechanism forpredicting/monitoring trust and adjusting update frequency over time.

SUMMARY

In an exemplary embodiment, the present invention provides acomputer-implemented autonomous agent operating method, the methodincluding configuring an autonomous agent for a task, launching theautonomous agent with an initial update interval, the initial updateinterval determining an initial frequency of the autonomous agentreporting results to a human user for review, and measuring a trustlevel of human user in a performance of the autonomous agent.

In another exemplary embodiment, the present invention provides acomputer program product for autonomous agent operating, the computerprogram product comprising a computer-readable storage medium havingprogram instructions embodied therewith, the program instructionsexecutable by a computer to cause the computer to perform: configuringan autonomous agent for a task, launching the autonomous agent with aninitial update interval, the initial update interval determining aninitial frequency of the autonomous agent reporting results to a humanuser for review, and measuring a trust level of human user in aperformance of the autonomous agent.

In another exemplary embodiment, the present invention provides anautonomous agent operating system, the system including a processor, anda memory, the memory storing instructions to cause the processor toperform: configuring an autonomous agent for a task, launching theautonomous agent with an initial update interval, the initial updateinterval determining an initial frequency of the autonomous agentreporting results to a human user for review, and measuring a trustlevel of human user in a performance of the autonomous agent.

Autonomous agents will increasingly take on tasks formerly requiringhuman action. Therefore, maximizing trust in these agents will lead toincreased adoption and use. And, effective management of these agentswill optimize results while minimizing interruptions and monitoringcosts. Thereby, the invention can reduce oversight costs associated withmonitoring agents in long running tasks.

Other details and embodiments of the invention will be described below,so that the present contribution to the art can be better appreciated.Nonetheless, the invention is not limited in its application to suchdetails, phraseology, terminology, illustrations and/or arrangements setforth in the description or shown in the drawings. Rather, the inventionis capable of embodiments in addition to those described and of beingpracticed and carried out in various ways and should not be regarded aslimiting.

As such, those skilled in the art will appreciate that the conceptionupon which this disclosure is based may readily be utilized as a basisfor the designing of other structures, methods and systems for carryingout the several purposes of the present invention. It is important,therefore, that the claims be regarded as including such equivalentconstructions insofar as they do not depart from the spirit and scope ofthe present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the invention will be better understood from the followingdetailed description of the exemplary embodiments of the invention withreference to the drawings, in which:

FIG. 1 exemplarily shows a high-level flow chart for an autonomous agentoperating method 100 according to an embodiment of the presentinvention;

FIG. 2 exemplarily depicts a system implementation of method 100according to an embodiment of the present invention;

FIG. 3 exemplarily depicts conceptual user experience (UX) elementsaccording to an embodiment of the present invention;

FIG. 4 depicts a cloud-computing node 10 according to an embodiment ofthe present invention;

FIG. 5 depicts a cloud-computing environment 50 according to anembodiment of the present invention; and

FIG. 6 depicts abstraction model layers according to an embodiment ofthe present invention.

DETAILED DESCRIPTION

The invention will now be described with reference to FIGS. 1-6, inwhich like reference numerals refer to like parts throughout. It isemphasized that, according to common practice, the various features ofthe drawings are not necessarily to scale. On the contrary, thedimensions of the various features can be arbitrarily expanded orreduced for clarity.

By way of introduction of the example depicted in FIG. 1, an embodimentof an autonomous agent operating method 100 according to the presentinvention can include various steps for autonomous agents providingupdates to their human owner or adjusting how and when these updates areperformed.

By way of introduction of the example depicted in FIG. 4, one or morecomputers of a computer system 12 according to an embodiment of thepresent invention can include a memory 28 having instructions stored ina storage system to perform the steps of FIG. 1.

Although one or more embodiments may be implemented in a cloudenvironment 50 (e.g., FIG. 6), it is nonetheless understood that thepresent invention can be implemented outside of the cloud environment.

With reference to FIGS. 1-3 and as discussed later in more detail, instep 101, an autonomous agent is configured for a task. For example,target ranges for acceptable transaction amounts may be set for an agentobtaining services, making purchase, or selling goods. Configuration byway of default settings and/or property dialogs is well known in theart.

In step 102, the autonomous agent is launched with an initial updateinterval, this interval determining the initial frequency of theautonomous agent reporting results to a human user for review. That is,an agent(s) is launched with initial update interval determined byspecified properties, past behavior, aspects of computational context,etc.

Consider the following exemplary approach to determining the initialupdate interval. First, a target value is selected by default. For atask that is expected to run for multiple hours, this initial intervalis set to 1 hour. For a task that is expected to run for multiple days,this initial interval is set to 1 day. If there is no furtherinformation about additional factors including the human user'spreferences, the value of agent results, the risk of agent failure, thenature of the computational domain within which the agent will berunning, etc., the agent is launched with this initial interval. Ifadditional information is available, it may be used to either decreaseor increase the initial interval. For example, high risk of agentfailure, high value of agent results, or unfamiliarity of computationaldomain, alone or in combination, may decrease the initial interval, witheach factor reducing the interval by a default amount which might be setat 15% per factor. Conversely, low risk of agent failure, low value ofagent results, or familiarity of computational domain, alone or incombination, may increase the initial interval by a default amount whichmight be set at 15% per factor. More complex algorithms for adjustingthis interval are also possible and easily envisioned by those skilledin the art.

In step 103, a trust level of human user in a performance of theautonomous agent is measured. That is, trust is monitored based oninterpretation of multiple user (and optionally agent) signals, analysisof past agent behavior, analysis of past and current computationalcontext, etc.

Consider the following exemplary approach to measuring the trust levelof a human user. Start with a default value of 50 on a hundred-pointscale, where 0 is minimum trust and 100 is maximum trust. If the humanuser requests an immediate update during an interval betweenautomatically-scheduled updates the trust level may be decreased by adefault amount which might be set at 10%. Conversely, if the human userdoes not inspect the results presented during an automatically-scheduledupdate the trust level may be increased by a default amount which mightbe set at 10%. In another case, if the human user manually adjusts theupdate interval to be more frequent the trust level may be decreased byeither the default value or by a value proportional to the magnitude ofthe manual adjustment. If the human user manually adjusts the updateinterval to be less frequent the trust level may be increased by eitherthe default value or by a value proportional to the magnitude of themanual adjustment. More complex algorithms for adjusting this trustvalue are also possible and easily envisioned by those skilled in theart.

And, in step 104, the current update interval is adjusted based on themeasured trust level. For example, the reporting interval may beincreased based on evidence of increased trust or the reporting intervalmay be decreased based on evidence of decreased trust (e.g., see FIG.2).

Via the method 100, long running agents automatically check back in withtheir human owner, providing status updates and/or intermediate resultson a schedule designed to maximize trust while minimizing interruptions.

The update schedule set at agent launch may be based on a number offactors including owner familiarity with the agent's past behavior,similarity of computational domain to past domains, the human owner'srisk tolerance, the human owner's computational or time budget, thecriticality of the agent's results, general agent profile settings, etc.The update schedule can be a default schedule (e.g., out-of-boxschedule) set by the provider and then adjusted by the human user foreach specific agent. That is, weights are associated with each factor inthe out-of-box schedule and the end user can adjust the weights based ontheir preference. This enables the invention to be used by those who arenot skilled in adjusting the weights (i.e., less sophisticated endusers) as well as those who want to adjust the weights for particularsituations. For example, an-out-of box schedule can include an algorithmto weigh each of the factors, the algorithm shown as equation (1):

Then, the end user can adjust the algorithm as shown in equation (2):

The update schedule may also automatically changes with time with morefrequent updates shortly after launch and less frequent updates as timegoes on. This may be particularly useful for agents that have not bedeployed before or for agents entering a computational domain unlikethose previously encountered (e.g., an agent familiar with simpleauctions entering a domain in which Dutch auctions are prevalent).

The inter-update interval may dynamically increase due to signalsindicating an increase in owner trust. Such signals may includeconfirmation of correct agent behavior, shortness of time devoted toobservation of reported results, the absence of requests for immediatestatus updates, etc.

The inter-update interval may also dynamically decrease due to signalsindicating a reduction in owner trust, such signals includingdispleasure with agent behavior, lengthy reviews of reported results,requests for immediate status updates, etc.

In one embodiment, the human owner can adjust the default-reportingschedule through the setting of agent properties. Properties can applyto all agents or only a subset of agents based on characteristics of theagents or the agent's computational context.

The interval for the next update can be based on elapsed time, amount ofcomputational resources consumed, number of successful actions, numberof unsuccessful actions etc.

The update schedule for a new agent can be adjusted to require lessfrequent (or no) updates for tasks similar to those successfully run inthe past (e.g., for a task that is launched once a week with the sameparameters and the same computational context).

In another embodiment, the update schedule for a new agent can beautomatically adjusted to require more frequent updates if thecomputational context is appreciably different (e.g., if a searchformerly conducted on English language sites is now launched on Japaneselanguage sites via a translator module).

The update schedule can be further adjusted dynamically based onagent-detected success indicators (e.g., number of highly rated searchresults, number of resources obtained at less than predicted costs etc.)if consistent with human owner's desires.

If multiple cooperating agents are involved in a shared task, then oneof them may be designated to synthesize a status update on aggregatemulti-agent behavior to minimize the overhead and complexity ofunderstanding the collective state (as contrasted with each agentreporting individually).

With respect to FIG. 3, FIG, 3 depicts a conceptual user-experience (UX)elements for adjusting agent properties, launching agents, reviewingagent status reports from an update, further managing the agent inresponse to an update, and manually adjusting the agent update schedulefor subsequent notifications.

Therefore, the method 100 improves over the conventional techniques byincluding a technique for autonomous agents providing updates to theirhuman owner, adjusting how this is done, and automatically modifyingagent-to-human notification schedule during long-running tasks. That is,no conventional technique includes the means to adjust autonomous agentnotification frequency in order to simultaneously maximize trust by theagent's human owner while minimizing the overhead of monitoring agentbehavior.

That is, research in agent trust is focused on agent to agent trust, oron manipulating the overall properties of an agent (e.g., emotionaltone, knowledgeability) to increase trust in an agent by a human. Someconventional techniques focused on trust formation note that the impactof frequency of interactions with a (human) service provider iscorrelated with increased relationship strength early on but not after amore extended period. But, this relationship is not manipulated, it hasnot been applied to autonomous agents, and no dynamic adjustment isprovided. Other conventional techniques in manipulating notificationfrequency allows for the setting of frequency by direct user means or bysensitivity to various factors including proximity (in time or space)and importance. Therefore, the method 100 improves on the prior art byincluding dynamic adjustment of notification frequency over time inrelation to measured trust by the human user in the agent or agents.

Exemplary Aspects, Using a Cloud Computing Environment

Although this detailed description includes an exemplary embodiment ofthe present invention in a cloud computing environment, it is to beunderstood that implementation of the teachings recited herein are notlimited to such a cloud computing environment. Rather, embodiments ofthe present invention are capable of being implemented in conjunctionwith any other type of computing environment now known or laterdeveloped.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client circuits through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating system , storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 4, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablenode and is not intended to suggest any limitation as to the scope ofuse or functionality of embodiments of the invention described herein.Regardless, cloud computing node 10 is capable of being implementedand/or performing any of the functionality set forth herein.

Although cloud computing node 10 is depicted as a computer system/server12, it is understood to be operational with numerous other generalpurpose or special purpose computing system environments orconfigurations. Examples of well-known computing systems, environments,and/or configurations that may be suitable for use with computersystem/server 12 include, but are not limited to, personal computersystems, server computer systems, thin clients, thick clients, hand-heldor laptop circuits, multiprocessor systems, microprocessor-basedsystems, set top boxes, programmable consumer electronics, network PCs,minicomputer systems, mainframe computer systems, and distributed cloudcomputing environments that include any of the above systems orcircuits, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingcircuits that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage circuits.

Referring now to FIG. 4, a computer system/server 12 is shown in theform general-purpose computing circuit. The components of computersystem/server 12 may include, but are not limited to, one or moreprocessors or processing units 16, a system memory 28, and a bus 18 thatcouples various system components including system memory 28 toprocessor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further described below, memory 28 mayinclude a computer program product storing one or program modules 42comprising computer readable instructions configured to carry out one ormore features of the present invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may be adapted for implementation in anetworking environment. In some embodiments, program modules 42 areadapted to generally carry out one or more functions and/ormethodologies of the present invention.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing circuit, other peripherals,such as display 24, etc and one or more components that facilitateinteraction with computer system/server 12. Such communication can occurvia Input/Output (I/O) interface 22, and/or any circuits (e.g., networkcard, modem, etc.) that enable computer system/server 12 to communicatewith one or more other computing circuits. For example, computersystem/server 12 can communicate with one or more networks such as alocal area network (LAN), a general wide area network (WAN), and/or apublic network (e.g., the Internet) via network adapter 20. As depicted,network adapter 20 communicates with the other components of computersystem/server 12 via bus 18. It should be understood that although notshown, other hardware and/or software components could be used inconjunction with computer system/server 12. Examples, include, but arenot limited to: microcode, circuit drivers, redundant processing units,external disk drive arrays, RAID systems, tape drives, and data archivalstorage systems, etc.

Referring now to FIG. 5, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing circuits used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingcircuit. It is understood that the types of computing circuits 54A-Nshown in FIG. 5 are intended to be illustrative only and that computingnodes 10 and cloud computing environment 50 can communicate with anytype of computerized circuit over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring now to FIG. 6, an exemplary set of functional abstractionlayers provided by cloud computing environment 50 (FIG. 5) is shown. Itshould be understood in advance that the components, layers, andfunctions shown in FIG. 6 are intended to be illustrative only andembodiments of the invention are not limited thereto. As depicted, thefollowing layers and corresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage circuits 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and an autonomous agent operating method 100in accordance with the present invention.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

Further, Applicant's intent is to encompass the equivalents of all claimelements, and no amendment to any claim of the present applicationshould be construed as a disclaimer of any interest in or right to anequivalent of any element or feature of the amended claim.

What is claimed is:
 1. A computer-implemented autonomous agent operating method, the method comprising: configuring an autonomous agent for a task; launching the autonomous agent with an initial update interval, the initial update interval determining an initial frequency of the autonomous agent reporting results to a human user for review; and measuring a trust level of human user in a performance of the autonomous agent.
 2. The method of claim 1, further comprising adjusting the update interval based on the measured trust level.
 3. The method of claim 2, wherein the update interval is dynamically adjusted in order to simultaneously maximize the trust by the human user while minimizing an overhead of monitoring behavior of the autonomous agent.
 4. The method of claim 1, wherein the initial update interval set at a launch of the agent is based on any of: an owner familiarity with a past behavior of the agent; a similarity of a computational domain to a past domain; a risk tolerance; a computational budget; a criticality of a result from the agent; and an agent profile setting.
 5. The method of claim 1, wherein the update interval automatically changes with time with more frequent updates after launch and less frequent updates after a predetermined amount of time.
 6. The method of claim 2, wherein the update interval is dynamically increased due to signals indicating an increase in owner trust or dynamically decreased due to signals indicating a decrease in owner trust.
 7. The computer-implemented method of claim 1, embodied in a cloud-computing environment.
 8. A computer program product for autonomous agent operating, the computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform: configuring an autonomous agent for a task; launching the autonomous agent with an initial update interval, the initial update interval determining an initial frequency of the autonomous agent reporting results to a human user for review; and measuring a trust level of human user in a performance of the autonomous agent.
 9. The computer program product of claim 8, further comprising adjusting the update interval based on the measured trust level.
 10. The computer program product of claim 9, wherein the update interval is dynamically adjusted in order to simultaneously maximize the trust by the human user while minimizing the overhead of monitoring behavior of the autonomous agent.
 11. The computer program product of claim 9, wherein the initial update interval set at a launch of the agent is based on any of: an owner familiarity with a past behavior of the agent; a similarity of a computational domain to a past domain; a risk tolerance; a computational budget; a criticality of a result from the agent; and an agent profile setting.
 12. The computer program product of claim 9, wherein the update interval automatically changes with time with more frequent updates after launch and less frequent updates after a predetermined amount of time.
 13. The computer program product of claim 10, wherein the update interval is dynamically increased due to signals indicating an increase in owner trust or dynamically decreased due to signals indicating a decrease in owner trust.
 14. An autonomous agent operating system, the system comprising: a processor; and a memory, the memory storing instructions to cause the processor to perform: configuring an autonomous agent for a task; launching the autonomous agent with an initial update interval, the initial update interval determining an initial frequency of the autonomous agent reporting results to a human user for review; and measuring a trust level of human user in a performance of the autonomous agent.
 15. The system of claim 14, further comprising adjusting the update interval based on the measured trust level.
 16. The system of claim 15, wherein the update interval is dynamically adjusted in order to simultaneously maximize the trust by the human user while minimizing an overhead of monitoring behavior of the autonomous agent.
 17. The system of claim 14, wherein the initial update interval set at a launch of the agent is based on any of: an owner familiarity with a past behavior of the agent; a similarity of a computational domain to a past domain; a risk tolerance; a computational budget; a criticality of a result from the agent; and an agent profile setting.
 18. The system of claim 14, wherein the update interval automatically changes with time with more frequent updates after launch and less frequent updates after a predetermined amount of time.
 19. The system of claim 15, wherein the update interval is dynamically increased due to signals indicating an increase in owner trust or dynamically decreased due to signals indicating a decrease in owner trust.
 20. The system of claim 14, embodied in a cloud-computing environment. 